stdp_synapse


Name:
stdp_synapse - Synapse type for spike-timing dependent  
plasticity.
Examples:
 
multiplicative STDP [2] mu_plus = mu_minus = 1.0
additive STDP [3] mu_plus = mu_minus = 0.0
Guetig STDP [1] mu_plus = mu_minus = [0.0,1.0]
van Rossum STDP [4] mu_plus = 0.0 mu_minus = 1.0

Description:
 
stdp_synapse is a connector to create synapses with spike time
dependent plasticity (as defined in [1]). Here the weight dependence
exponent can be set separately for potentiation and depression.

Parameters:
 
tau_plus double - Time constant of STDP window, potentiation in ms
(tau_minus defined in post-synaptic neuron)
lambda double - Step size
alpha double - Asymmetry parameter (scales depressing increments as
alpha*lambda)
mu_plus double - Weight dependence exponent, potentiation
mu_minus double - Weight dependence exponent, depression
Wmax double - Maximum allowed weight

Transmits:
SpikeEvent  

References:
 
[1] Guetig et al. (2003) Learning Input Correlations through Nonlinear
Temporally Asymmetric Hebbian Plasticity. Journal of Neuroscience

[2] Rubin, J., Lee, D. and Sompolinsky, H. (2001). Equilibrium
properties of temporally asymmetric Hebbian plasticity, PRL
86,364-367

[3] Song, S., Miller, K. D. and Abbott, L. F. (2000). Competitive
Hebbian learning through spike-timing-dependent synaptic
plasticity,Nature Neuroscience 3:9,919--926

[4] van Rossum, M. C. W., Bi, G-Q and Turrigiano, G. G. (2000).
Stable Hebbian learning from spike timing-dependent
plasticity, Journal of Neuroscience, 20:23,8812--8821

Author:
Moritz Helias, Abigail Morrison  
Adapted by: Philipp Weidel
FirstVersion:
March 2006  
SeeAlso: Source:
/home/nest/work/nest-2.14.0/models/stdp_connection.h